Gerard Wagemaker

6.2k citations
146 papers · 4.2k indexed · h-index 39
  • Hematology top 0.5%
    • Hematopoietic Stem Cell Transplantation 49
    • Platelet Disorders and Treatments 18
    • Acute Myeloid Leukemia Research 16
  • Immunology top 2%
    • Immune Cell Function and Interaction 22
    • Immune Response and Inflammation 17
  • Genetics top 2%
    • Virus-based gene therapy research 34
    • Mesenchymal stem cell research 16
  • Genetics top 2%
    • Virus-based gene therapy research 34
    • Mesenchymal stem cell research 16
  • Oncology top 5%
    • RNA Interference and Gene Delivery 18

Gerard Wagemaker

143 papers receiving 4.0k citations

Peers

Gerard Wagemaker
Comparison fields: 5 of 114
  • Hematology 1.5k
  • Immunology 1.1k
  • Genetics 465
  • Genetics 1.1k
  • Oncology 883
Replace KM Zsebo with:
KM Zsebo United States
P Mannoni France
Tobias Gedde‐Dahl Norway
Laure Coulombel France
Ivan Bertoncello Australia
T. M. Dexter United Kingdom
T. R. Bradley Australia
CI Civin United States
George Kannourakis Australia
JD Griffin United States
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Citations per field
00.5×2.8×
KM Zsebo · 1×
Citations per year

Countries citing papers authored by Gerard Wagemaker

Since Specialization
Citations

This map shows the geographic impact of Gerard Wagemaker's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Gerard Wagemaker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gerard Wagemaker more than expected).

Fields of papers citing papers by Gerard Wagemaker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gerard Wagemaker. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Gerard Wagemaker. The network helps show where Gerard Wagemaker may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Gerard Wagemaker, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gerard Wagemaker Line = papers co-authored together Gerard Wagemaker links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201816
2 20171
3 20174
4 201323
5 201346
6 20128
7 201213
8 201126
9 200734
10 200753
11 200261
12 19981
13 199817
14 199732
15 199627
16 199546
17 199210
18 199143
19 19907
20 198874

About Gerard Wagemaker

Gerard Wagemaker is a scholar working on Hematology, Genetics, Immunology, Genetics and Oncology, having authored 146 papers that have together received 4.2k indexed citations. Recurring topics across this work include Hematopoietic Stem Cell Transplantation (49 papers), Virus-based gene therapy research (34 papers), Immune Cell Function and Interaction (22 papers), RNA Interference and Gene Delivery (18 papers), Platelet Disorders and Treatments (18 papers), Immune Response and Inflammation (17 papers), Acute Myeloid Leukemia Research (16 papers) and Mesenchymal stem cell research (16 papers). The work is most often cited by research in Hematology (1.5k citations), Immunology (1.1k citations), Genetics (465 citations), Genetics (1.1k citations) and Oncology (883 citations). Gerard Wagemaker has collaborated with scholars based in Netherlands, United States and Germany. Frequent co-authors include Bob Löwenberg, AW Wognum, Trudi P. Visser, Monique M.A. Verstegen, Lambert C. J. Dorssers, Albertus W. Wognum, Ruud Delwel, Frank J. T. Staal, D. W. van Bekkum and Karen J. Neelis. Their work appears in journals such as Blood, Leukemia, Stem Cells, Experimental Hematology and Human Gene Therapy.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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